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ITHACA, N.Y. – Personal sensor data could help monitor and relieve stress among local doctors, although privacy concerns about who sees the information and for what purposes need to be addressed, according to a collaborative study from Cornell Tech.
Burnout in all kinds of jobs is on the rise in the US, where the “Great Resignation” and the “quiet exit” have entered the lexicon in recent years. This is especially true in the healthcare industry, which has been strained beyond measure by the COVID-19 pandemic.
Stress is both physical and mental, and evidence of stress can be measured through the use of smartphones, wearables and personal computers. But the collection and analysis of data—and the larger questions of who should have access to that information and for what purpose—raise myriad sociotechnical questions.
“We looked at whether we could measure stress in workplaces using these kinds of devices, but do these people really want this kind of system? That was the motivation for us to talk to these actual workers,” said Daniel Adler, lead author with fellow doctoral student Emily Tseng of “Burnout and the Quantified Workplace: Tensions Around Personal Sensing Stress Interventions in Resident Physicians,” published Nov. 11 ACM Proceedings on Human-Computer Interaction.
The paper is being presented at the ACM Conference on Computer-Supported Cooperative Work (CSCW) and Social Computing, nearly Nov. 8-22.
Adler and Tseng worked with senior author Tanzim Choudhury, the Roger and Joel Burnell Professor of Integrative Health and Technology at the Jacobs Technion-Cornell Institute at Cornell Tech. Fellows come from the Zucker School of Medicine at Hofstra/Northwell Health and Zucker Hillside Hospital.
A resident physician’s work environment is slightly different from a traditional apprenticeship situation in that their supervisor, the attending physician, is also their mentor. This can blur the lines between the two.
“It’s a new context,” Tseng said. “We don’t really know what the actual boundaries are there or what it looks like when you introduce these new technologies. So you have to try and decide what those norms might be to determine if that information flow is appropriate in the first place.
Choudhury and her group addressed these issues through a study involving local physicians at a New York city hospital. After hour-long Zoom resident interviews, residents and their staff received mock-ups of a resident well-being tracker, a dashboard with behavioral data on residents’ sleep, activity and work hours; data on resident burnout levels; and a text field where residents can characterize their well-being.
Tseng said residents are open to the idea of using technology to improve well-being. “They were also very interested in the issue of privacy,” she said, “and how we can use technologies like this to achieve these positive goals while balancing privacy concerns.”
The study included two intersecting use cases: self-reflection, in which residents review their behavioral data, and data sharing, in which the same information is shared with their staff and program directors for intervention purposes.
Among the key findings: Residents were hesitant to share their data, unsure that supervisors would use it to improve their well-being. There is also the issue of anonymity, which is more likely with more involvement. But greater participation would hurt the program’s potential usefulness because supervisors would not be able to identify which residents are struggling.
“This process of sharing personal data is somewhat complicated,” Adler said. “There’s a lot of interesting ongoing work we’re involved in that looks at the issue of privacy and how you represent yourself through your data in more traditional mental health settings. It’s not as simple as, ‘They’re my doctor, so I’m comfortable sharing this data.'”
The authors conclude by referring to the “urgent need for further work to establish new norms around data-driven workplace well-being management solutions that better center workers’ needs and provide protections for workers who intend to support”.
Other collaborators include Emmanuel Moss, a postdoctoral fellow at Cornell Tech; David Mohr, professor at Northwestern University Feinberg School of Medicine; as well as Dr. John Kane, Dr. John Young, and Dr. Hatiya Moon of Zucker Hillside Hospital.
The research was supported by grants from the National Institute of Mental Health, the National Science Foundation and the Digital Life Initiative at Cornell Tech.
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Journal
ACM Proceedings on Human-Computer Interaction
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